1. Technical Field
The present invention relates to target tracking systems, and more particularly deals with a tracking system that simultaneously uses both a correlation tracker and an object tracker.
2. Discussion
The functional purpose of a tracking system is to continuously track one or more selected targets in a scene. A tracking system must continuously maintain lock on, or track a target, even under unfavorable scene conditions. Tracking systems devised in the past have utilized object trackers and correlation trackers but have used them independently of one another. When operating independently both types of trackers have disadvantages which render them susceptible to a loss of lock or a break in target tracking.
An object tracker is one which tracks discrete targets individually and explicitly. Tracking is achieved by forming a closely fitting two-dimensional exclusionary enclosure around each target to be tracked in a digitized image. Such a target enclosure is known as a track gate. A track gate isolates a tracked target from other potentially interfering objects in the digitized image. An object tracker operates upon the digitized image within the track gate to generate a precisely defined target trackpoint. In some cases the precisely defined target trackpoint represents the centroid of the silhouette of the tracked target. Potentially interfering objects are generally referred to as background clutter. Tracking gate growth algorithms are provided within an object tracker to enable the track gate to independently and continuously adapt to the changing size and aspect ratio of targets tracked by the object tracker.
In an object tracker, useful information is derived only from the digitized image enclosed within the track gate. An object tracker is sensitive to the adverse effects of background clutter. The tracked target may be lost when clutter enters the track gate and merges with the tracked target, or obscures a significant part of the tracked target. Clutter can cause a target trackpoint to wander away from the initially acquired target if the size of the track gate is too large. The primary mechanism responsible for "gate stealing" or an object tracker breaking its "lock" on a target, is the track gate growth algorithm which is necessary to accommodate dimensional changes of a target over a series of images. The target trackpoint may also be lost if there is severe input sensor LOS motion "jerking" the target out of the track gate. Experience with object trackers has shown them to be relatively susceptible to clutter induced loss of lock or gate stealing. Whenever this phenomenon occurs, recovery from the ensuing loss of lock is nearly impossible.
The second type of tracker used independently in the past is a correlation tracker. A correlation tracker differs conceptually and fundamentally from an object tracker. A correlation tracker operates by repeatedly and periodically comparing a currently digitized image to a stored reference region image or "template image". A point whose coordinates are known with respect to the center of the template image is defined to be a background reference point. The correlation tracker locates the background reference point in the currently digitized image by finding a portion of the current image which matches the reference image region. A correlation tracker generally tracks patterns rather than discrete or individual targets. Trackable patterns include background details as well as patterns or groups of specific objects. Any type of scene material, texture or structure may be tracked providing that the pattern is unique and temporally repeatable. A large discrete target can be tracked explicitly by a correlation tracker only if the target possesses a unique and visible pattern of internal texture or edge detail. Although a correlation tracker cannot track a small stationary target explicitly, such a target can be tracked implicitly as part of a larger scene.
A correlation tracker operating independently unfortunately has its share of disadvantages. A correlation tracker can only track accurately if its reference region image matches up well to a portion of the current digitized image. Since a correlation tracker tracks by matching a stored reference region image with a current digitized image, it cannot track a changing scene indefinitely without renewing or "updating" its reference region image with current data. When a correlation tracker's reference region image data no longer matches data from the current digitized image, the correlation tracker's accuracy deteriorates. However, the process of updating a reference region image introduces error or "noise" into the correlation tracker. Typically, the error or noise is accumulated and does not have a zero mean value. Therefore, a form of "Brownian motion", or "random walk" is introduced into the background reference point generated by a correlation tracker. The amount of error, or the extent of the random walk problem, depends directly on the average update rate of the reference region image. The accumulated error may ultimately cause the correlation tracker's background reference point to drift away from its original position in the scene. A correlation tracker will suffer a loss of lock if the tracked scene is jerked out of the field of view of the input sensor, or if the live scene changes so rapidly that the process of updating the reference region image cannot accommodate the change. The difficulty with a rapidly changing scene can be overcome by frequently updating the correlation tracker's reference region image. The difficulty with severe sensor motion can be overcome if the tracked scene later enters the field of view of the input sensor, because correlation tracking will resume instantaneously, with the same background reference point as before. While it is possible to overcome these difficulties, it would be preferable not to have to deal with them in the first place.